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Mature model measures up

Putting a model-based or simulation-based software system that can answer a lot of important questions at a facility is “very doable”, according to MSi Kenny president Michael Mai. “Those value-adding questions will be different for every facility,” he says.

Because it is component based, Mai says his company’s software is easy to customise for different situations and locations. Offline components include ES (engineering simulator) and Train (training simulator), while online components include Monitor (monitors production systems), Advise (predicts adverse conditions), VMS (virtual metering system that calculates flow rates), Control (for gas production and blending), and Optimize (real-time simulation).

“Now we know how the facility is behaving, now I can give you real-time information that is relevant,” Mai declares.

The software system that became Virtuoso was created 18 years ago as a closed-loop online control system for North Sea operations. It was all model based.

“It started primarily looking at liquids slugging,” recalls Mai, one of four founders of MSi Kenny. “The package began by modelling those pipelines and forecasting out whether they would have slugging. When they saw that was possible, we started looking at things like tubing head pressure control and compressor fuel gas optimisation.”

The Virtuoso software has evolved over the years to simulate “well models, pipeline models, and unit operations such as valves, compression, separators and pumps”, he says, adding that the list extends to anything from the sand face, through the well, gathering systems, topsides, trunklines, and shore-based facilities.

“The software allows you to take an asset, and once you have commissioned the system, still be thinking about flow assurance,” says Mai, who holds a PhD in chemical engineering. It is possible to look at high and low production cases, he says, and simulate how paraffins, hydrates and the like will behave in each case. At its heart, Virtuoso is a blend of simulation tools. “Because we have that in a single package, we can do an integrated model,” Mai says, explaining some of the system’s advantages.

A critical issue with any software, he adds, is that it must be reliable. “With a lot of design simulation tools, the focus is to pack new theory into the tool. The presumption is it must be better because it’s new. But it’s crashing. A facility needs to run 24/7. The nature of these is very complicated.”

MSi Kenny designed Virtuoso for online use “so our code structure and methodologies are all driven around robustness and speed”, he adds.

Another criterion is the data presented to the software for computation. There is a delicate balance to be struck with quality and quantity of meters and other information-gathering instruments.

“The fewer instruments you have, the less accurate my prediction will be. The more instruments you have, usually the better the predictions can become,” Mai explains. “Now there’s so much at risk that putting a system in place is a minimal investment versus the potential returns.

“The practical reality is you can only know so much [about a field],” he adds. “The industry has to come to grips with what is knowable, and at some point having a better model is not going to help you.”

Mature model measures up

Mature model measures up

Putting a model-based or simulation-based software system that can answer a lot of important questions at a facility is “very doable”, according to MSi Kenny president Michael Mai. “Those value-adding questions will be different for every facility,” he says.

Because it is component based, Mai says his company’s software is easy to customise for different situations and locations. Offline components include ES (engineering simulator) and Train (training simulator), while online components include Monitor (monitors production systems), Advise (predicts adverse conditions), VMS (virtual metering system that calculates flow rates), Control (for gas production and blending), and Optimize (real-time simulation).

“Now we know how the facility is behaving, now I can give you real-time information that is relevant,” Mai declares.

The software system that became Virtuoso was created 18 years ago as a closed-loop online control system for North Sea operations. It was all model based.

“It started primarily looking at liquids slugging,” recalls Mai, one of four founders of MSi Kenny. “The package began by modelling those pipelines and forecasting out whether they would have slugging. When they saw that was possible, we started looking at things like tubing head pressure control and compressor fuel gas optimisation.”

The Virtuoso software has evolved over the years to simulate “well models, pipeline models, and unit operations such as valves, compression, separators and pumps”, he says, adding that the list extends to anything from the sand face, through the well, gathering systems, topsides, trunklines, and shore-based facilities.

“The software allows you to take an asset, and once you have commissioned the system, still be thinking about flow assurance,” says Mai, who holds a PhD in chemical engineering. It is possible to look at high and low production cases, he says, and simulate how paraffins, hydrates and the like will behave in each case. At its heart, Virtuoso is a blend of simulation tools. “Because we have that in a single package, we can do an integrated model,” Mai says, explaining some of the system’s advantages.

A critical issue with any software, he adds, is that it must be reliable. “With a lot of design simulation tools, the focus is to pack new theory into the tool. The presumption is it must be better because it’s new. But it’s crashing. A facility needs to run 24/7. The nature of these is very complicated.”

MSi Kenny designed Virtuoso for online use “so our code structure and methodologies are all driven around robustness and speed”, he adds.

Another criterion is the data presented to the software for computation. There is a delicate balance to be struck with quality and quantity of meters and other information-gathering instruments.

“The fewer instruments you have, the less accurate my prediction will be. The more instruments you have, usually the better the predictions can become,” Mai explains. “Now there’s so much at risk that putting a system in place is a minimal investment versus the potential returns.

“The practical reality is you can only know so much [about a field],” he adds. “The industry has to come to grips with what is knowable, and at some point having a better model is not going to help you.”

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